Energy and Service-Priority aware Trajectory Design for UAV-BSs using Double Q-Learning

2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC) ◽

10.1109/ccnc49032.2021.9369472 ◽

2021 ◽

Author(s):

Sayed Amir Hoseini ◽

Ayub Bokani ◽

Jahan Hassan ◽

Shavbo Salehi ◽

Salil S. Kanhere

Keyword(s):

Trajectory Design ◽

Service Priority

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Learning to Rest: A Q-Learning Approach to Flying Base Station Trajectory Design with Landing Spots

2018 52nd Asilomar Conference on Signals, Systems, and Computers ◽

10.1109/acssc.2018.8645103 ◽

2018 ◽

Author(s):

Harald Bayerlein ◽

Rajeev Gangula ◽

David Gesbert

Keyword(s):

Base Station ◽

Learning Approach ◽

Trajectory Design ◽

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Optimized Trajectory Design in UAV Based Cellular Networks: A Double Q-Learning Approach

2018 IEEE International Conference on Communication Systems (ICCS) ◽

10.1109/iccs.2018.8689249 ◽

2018 ◽

Author(s):

Xuanlin Liu ◽

Mingzhe Chen ◽

Changchuan Yin

Keyword(s):

Cellular Networks ◽

Learning Approach ◽

Trajectory Design ◽

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Q-learning based Service Function Chaining using VNF Resource-aware Reward Model

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) ◽

10.23919/apnoms50412.2020.9236975 ◽

2020 ◽

Author(s):

Doyoung Lee ◽

Jae-Hyoung Yoo ◽

James Won-Ki Hong

Keyword(s):

Service Function ◽

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Energy-efficient UAV trajectory design for backscatter communication: A deep reinforcement learning approach

China Communications ◽

10.23919/jcc.2020.10.009 ◽

2020 ◽

Vol 17 (10) ◽

pp. 129-141

Author(s):

Yiwen Nie ◽

Junhui Zhao ◽

Jun Liu ◽

Jing Jiang ◽

Ruijin Ding

Keyword(s):

Reinforcement Learning ◽

Energy Efficient ◽

Learning Approach ◽

Trajectory Design ◽

Backscatter Communication

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Q-learning Based Radio Channels Utility Evaluation Algorithm for the Local Dynamic Spectrum Management in Mobile Ad-hoc Networks

2020 Baltic URSI Symposium (URSI) ◽

10.23919/ursi48707.2020.9254037 ◽

2020 ◽

Author(s):

Krzysztof Malon ◽

Jerzy Lopatka ◽

Pawel Skokowski

Keyword(s):

Ad Hoc ◽

Spectrum Management ◽

Dynamic Spectrum ◽

Local Dynamic ◽

Dynamic Spectrum Management ◽

Evaluation Algorithm ◽

Utility Evaluation ◽

Mobile Ad Hoc ◽

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Prioritized epoch-incremental Q-learning algorithm

Theoretical and Applied Informatics ◽

10.2478/v10179-012-0008-1 ◽

2012 ◽

Vol 24 (2) ◽

Author(s):

Roman Zajdel

Keyword(s):

Learning Algorithm ◽

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Applying Q-Learning in intrusion policy prediction based on preferences on advanced persistent threats

Advances in Management Engineering and Information Technology ◽

10.2495/ameit140841 ◽

2015 ◽

Author(s):

S.H. Chien ◽

C.S. Ho ◽

C.H. Chen

Keyword(s):

Advanced Persistent Threats

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Low-Thrust Trajectory Design for a Low-Cost Multiple Asteroid Rendezvous and Sample Return Mission

10.2514/6.iac-04-q.p.20 ◽

2004 ◽

Keyword(s):

Low Cost ◽

Trajectory Design ◽

Sample Return ◽

Sample Return Mission

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Q-learning System Based on Cooperative Least Squares Support Vector Machine

ACTA AUTOMATICA SINICA ◽

10.3724/sp.j.1004.2009.00214 ◽

2009 ◽

Vol 35 (2) ◽

pp. 214-219 ◽

Author(s):

Xue-Song WANG ◽

Xi-Lan TIAN ◽

Yu-Hu CHENG ◽

Jian-Qiang YI

Keyword(s):

Support Vector Machine ◽

Least Squares ◽

Learning System ◽

Support Vector ◽

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Application of improved Q learning algorithm to job shop problem

Journal of Computer Applications ◽

10.3724/sp.j.1087.2008.03268 ◽

2009 ◽

Vol 28 (12) ◽

pp. 3268-3270

Author(s):

Chao WANG ◽

Jing GUO ◽

Zhen-qiang BAO

Keyword(s):

Job Shop ◽

Learning Algorithm ◽

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